Opto-Electronic Engineering, Volume. 51, Issue 4, 240025-1(2024)

PAW-YOLOv7: algorithm for detection of tiny floating objects in river channels

Qinglei Luan1,2, Xinyu Chang1,2, Ye Wu1,2, Conglong Deng1,2、*, Yanqiong Shi1,2, and Zihua Chen1,2
Author Affiliations
  • 1School of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei, Anhui 230601, China
  • 2Anhui Province Key Laboratory of Intelligent Manufacturing of Construction Machinery, Hefei, Anhui 230601, China
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    References(31)

    [2] Zhu H, Zhou S Y, Liu X et al. Survey of single-stage object detection algorithms based on deep learning[J]. Ind Control Comput, 36, 101-103(2023).

    [16] Li C, Zhou A J, Yao A B. Omni-dimensional dynamic convolution[C](2022).

    [23] Yang B, Bender G, Le Q V et al. CondConv: conditionally parameterized convolutions for efficient inference[C], 117(2019).

    [31] Zhang H Y, Cissé M, Dauphin Y N et al. mixup: Beyond empirical risk minimization[C](2017).

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    Qinglei Luan, Xinyu Chang, Ye Wu, Conglong Deng, Yanqiong Shi, Zihua Chen. PAW-YOLOv7: algorithm for detection of tiny floating objects in river channels[J]. Opto-Electronic Engineering, 2024, 51(4): 240025-1

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    Paper Information

    Category: Article

    Received: Jan. 25, 2024

    Accepted: Mar. 12, 2024

    Published Online: Jul. 8, 2024

    The Author Email: Conglong Deng (邓从龙)

    DOI:10.12086/oee.2024.240025

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